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Ding J, Li J, Zhang C, Tan L, Zhao C, Gao L. High-Throughput Combined Analysis of Saliva Microbiota and Metabolomic Profile in Chinese Periodontitis Patients: A Pilot Study. Inflammation 2024; 47:874-890. [PMID: 38148454 DOI: 10.1007/s10753-023-01948-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Revised: 11/28/2023] [Accepted: 12/11/2023] [Indexed: 12/28/2023]
Abstract
The onset and progression of periodontitis involves complicated interactions between the dysbiotic oral microbiota and disrupted host immune-inflammatory response, which can be mirrored by the changes in salivary metabolites profile. This pilot study sought to examine the saliva microbiome and metabolome in the Chinese population by the combined approach of 16s rRNA sequencing and high-throughput targeted metabolomics to discover potential cues for host-microbe metabolic interactions. Unstimulated whole saliva samples were collected from eighteen Stage III and IV periodontitis patients and thirteen healthy subjects. Full-mouth periodontal parameters were recorded. The taxonomic composition of microbiota was obtained by 16s rRNA sequencing, and the metabolites were identified and measured by ultra-high performance liquid chromatography and mass spectrometry-based metabolomic analysis. The oral microbiota composition displayed marked changes where the abundance of 93 microbial taxa differed significantly between the periodontitis and healthy group. Targeted metabolomics identified 103 differential metabolites between the patients and healthy individuals. Functional enrichment analysis demonstrated the upregulation of protein digestion and absorption, histidine metabolism, and nicotinate and nicotinamide metabolism pathways in the dysbiotic microbiota, while the ferroptosis, tryptophan metabolism, glutathione metabolism, and carbon metabolism pathways were upregulated in the patients. Correlation analysis confirmed positive relationships between the clinical parameters, pathogen abundances, and disease-related metabolite levels. The integral analysis of the saliva microbiome and metabolome yielded an accurate presentation of the dysbiotic oral microbiome and functional alterations in host-microbe metabolism. The microbial and metabolic profiling of the saliva could be a potential tool in the diagnosis, prognosis evaluation, and pathogenesis study of periodontitis.
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Affiliation(s)
- Jing Ding
- Hospital of Stomatology, Sun Yat-Sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Stomatology, Guangzhou, China
- Guanghua School of Stomatology, Sun Yat-Sen University, Guangzhou, China
| | - Jinyu Li
- Hospital of Stomatology, Sun Yat-Sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Stomatology, Guangzhou, China
- Guanghua School of Stomatology, Sun Yat-Sen University, Guangzhou, China
| | - Chi Zhang
- Hospital of Stomatology, Sun Yat-Sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Stomatology, Guangzhou, China
- Guanghua School of Stomatology, Sun Yat-Sen University, Guangzhou, China
| | - Lingping Tan
- Hospital of Stomatology, Sun Yat-Sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Stomatology, Guangzhou, China
- Guanghua School of Stomatology, Sun Yat-Sen University, Guangzhou, China
| | - Chuanjiang Zhao
- Hospital of Stomatology, Sun Yat-Sen University, Guangzhou, China.
- Guangdong Provincial Key Laboratory of Stomatology, Guangzhou, China.
- Guanghua School of Stomatology, Sun Yat-Sen University, Guangzhou, China.
| | - Li Gao
- Hospital of Stomatology, Sun Yat-Sen University, Guangzhou, China.
- Guangdong Provincial Key Laboratory of Stomatology, Guangzhou, China.
- Guanghua School of Stomatology, Sun Yat-Sen University, Guangzhou, China.
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Pitchika V, Büttner M, Schwendicke F. Artificial intelligence and personalized diagnostics in periodontology: A narrative review. Periodontol 2000 2024; 95:220-231. [PMID: 38927004 DOI: 10.1111/prd.12586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 04/29/2024] [Accepted: 06/07/2024] [Indexed: 06/28/2024]
Abstract
Periodontal diseases pose a significant global health burden, requiring early detection and personalized treatment approaches. Traditional diagnostic approaches in periodontology often rely on a "one size fits all" approach, which may overlook the unique variations in disease progression and response to treatment among individuals. This narrative review explores the role of artificial intelligence (AI) and personalized diagnostics in periodontology, emphasizing the potential for tailored diagnostic strategies to enhance precision medicine in periodontal care. The review begins by elucidating the limitations of conventional diagnostic techniques. Subsequently, it delves into the application of AI models in analyzing diverse data sets, such as clinical records, imaging, and molecular information, and its role in periodontal training. Furthermore, the review also discusses the role of research community and policymakers in integrating personalized diagnostics in periodontal care. Challenges and ethical considerations associated with adopting AI-based personalized diagnostic tools are also explored, emphasizing the need for transparent algorithms, data safety and privacy, ongoing multidisciplinary collaboration, and patient involvement. In conclusion, this narrative review underscores the transformative potential of AI in advancing periodontal diagnostics toward a personalized paradigm, and their integration into clinical practice holds the promise of ushering in a new era of precision medicine for periodontal care.
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Affiliation(s)
- Vinay Pitchika
- Department of Conservative Dentistry and Periodontology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Martha Büttner
- Department of Oral Diagnostics, Digital Health and Health Services Research, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Falk Schwendicke
- Department of Conservative Dentistry and Periodontology, LMU University Hospital, LMU Munich, Munich, Germany
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Chu Z, Zhao T, Zhang Z, Chu CH, Cai K, Wu J, Wu W, Tang C. Untargeted Metabolomics Analysis of Gingival Tissue in Patients with Severe Periodontitis. J Proteome Res 2024; 23:3-15. [PMID: 38018860 DOI: 10.1021/acs.jproteome.3c00105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2023]
Abstract
The purpose of this study was to determine potential metabolic biomarkers and therapeutic drugs in the gingival tissue of individuals with periodontitis. Liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) were used to analyze the gingival tissue samples from 20 patients with severe periodontitis and 20 healthy controls. Differential metabolites were identified using variable important in projection (VIP) values from the orthogonal partial least squares discrimination analysis (OPLS-DA) model and then verified for significance between groups using a two-tailed Student's t test. In total, 65 metabolites were enriched in 33 metabolic pathways, with 40 showing a significant increase and 25 expressing a significant decrease. In addition, it was found that patients with severe periodontitis have abnormalities in metabolic pathways, such as glucose metabolism, purine metabolism, amino acid metabolism, and so on. Furthermore, based on a multidimensional analysis, 12 different metabolites may be the potential biomarkers of severe periodontitis. The experiment's raw data have been uploaded to the MetaboLights database, and the project number is MTBLS8357. Moreover, osteogenesis differentiation characteristics were detected in the selected metabolites. The findings may provide a basis for the study of diagnostic biomarkers and therapeutic metabolites in severe periodontitis.
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Affiliation(s)
- Zhuangzhuang Chu
- Department of Dental Implantology, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing 210029, China
- Jiangsu Key Laboratory of Oral Diseases,Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing 210029, China
| | - Tong Zhao
- Department of Dental Implantology, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing 210029, China
- Jiangsu Key Laboratory of Oral Diseases,Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing 210029, China
| | - Zhewei Zhang
- Department of Dental Implantology, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing 210029, China
- Jiangsu Key Laboratory of Oral Diseases,Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing 210029, China
| | - Catherine Huihan Chu
- Department of Orthodontic, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing 210029, China
- Jiangsu Key Laboratory of Oral Diseases,Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing 210029, China
| | - Kunzhan Cai
- Department of Dental Implantology, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing 210029, China
- Jiangsu Key Laboratory of Oral Diseases,Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing 210029, China
| | - Jin Wu
- Department of Dental Implantology, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing 210029, China
- Jiangsu Key Laboratory of Oral Diseases,Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing 210029, China
| | - Wei Wu
- Department of Dental Implantology, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing 210029, China
- Jiangsu Key Laboratory of Oral Diseases,Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing 210029, China
| | - Chunbo Tang
- Department of Dental Implantology, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing 210029, China
- Jiangsu Key Laboratory of Oral Diseases,Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing 210029, China
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Adeoye J, Su YX. Artificial intelligence in salivary biomarker discovery and validation for oral diseases. Oral Dis 2024; 30:23-37. [PMID: 37335832 DOI: 10.1111/odi.14641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 05/19/2023] [Accepted: 05/28/2023] [Indexed: 06/21/2023]
Abstract
Salivary biomarkers can improve the efficacy, efficiency, and timeliness of oral and maxillofacial disease diagnosis and monitoring. Oral and maxillofacial conditions in which salivary biomarkers have been utilized for disease-related outcomes include periodontal diseases, dental caries, oral cancer, temporomandibular joint dysfunction, and salivary gland diseases. However, given the equivocal accuracy of salivary biomarkers during validation, incorporating contemporary analytical techniques for biomarker selection and operationalization from the abundant multi-omics data available may help improve biomarker performance. Artificial intelligence represents one such advanced approach that may optimize the potential of salivary biomarkers to diagnose and manage oral and maxillofacial diseases. Therefore, this review summarized the role and current application of techniques based on artificial intelligence for salivary biomarker discovery and validation in oral and maxillofacial diseases.
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Affiliation(s)
- John Adeoye
- Division of Oral and Maxillofacial Surgery, Faculty of Dentistry, University of Hong Kong, Hong Kong SAR, China
| | - Yu-Xiong Su
- Division of Oral and Maxillofacial Surgery, Faculty of Dentistry, University of Hong Kong, Hong Kong SAR, China
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Blanco-Pintos T, Regueira-Iglesias A, Seijo-Porto I, Balsa-Castro C, Castelo-Baz P, Nibali L, Tomás I. Accuracy of periodontitis diagnosis obtained using multiple molecular biomarkers in oral fluids: A systematic review and meta-analysis. J Clin Periodontol 2023; 50:1420-1443. [PMID: 37608638 DOI: 10.1111/jcpe.13854] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 06/21/2023] [Accepted: 06/29/2023] [Indexed: 08/24/2023]
Abstract
AIM To determine the accuracy of biomarker combinations in gingival crevicular fluid (GCF) and saliva through meta-analysis to diagnose periodontitis in systemically healthy subjects. METHODS Studies on combining two or more biomarkers providing a binary classification table, sensitivity/specificity values or group sizes in subjects diagnosed with periodontitis were included. The search was performed in August 2022 through PUBMED, EMBASE, Cochrane, LILACS, SCOPUS and Web of Science. The methodological quality of the articles selected was evaluated using the QUADAS-2 checklist. Hierarchical summary receiver operating characteristic modelling was employed to perform the meta-analyses (CRD42020175021). RESULTS Twenty-one combinations in GCF and 47 in saliva were evaluated. Meta-analyses were possible for six salivary combinations (median sensitivity/specificity values): IL-6 with MMP-8 (86.2%/80.5%); IL-1β with IL-6 (83.0%/83.7%); IL-1β with MMP-8 (82.7%/80.8%); MIP-1α with MMP-8 (71.0%/75.6%); IL-1β, IL-6 and MMP-8 (81.8%/84.3%); and IL-1β, IL-6, MIP-1α and MMP-8 (76.6%/79.7%). CONCLUSIONS Two-biomarker combinations in oral fluids show high diagnostic accuracy for periodontitis, which is not substantially improved by incorporating more biomarkers. In saliva, the dual combinations of IL-1β, IL-6 and MMP-8 have an excellent ability to detect periodontitis and a good capacity to detect non-periodontitis. Because of the limited number of biomarker combinations evaluated, further research is required to corroborate these observations.
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Affiliation(s)
- T Blanco-Pintos
- Oral Sciences Research Group, Special Needs Unit, Department of Surgery and Medical-Surgical Specialties, School of Medicine and Dentistry, Universidade de Santiago de Compostela, Health Research Institute of Santiago (IDIS), Santiago de Compostela, Spain
| | - A Regueira-Iglesias
- Oral Sciences Research Group, Special Needs Unit, Department of Surgery and Medical-Surgical Specialties, School of Medicine and Dentistry, Universidade de Santiago de Compostela, Health Research Institute of Santiago (IDIS), Santiago de Compostela, Spain
| | - I Seijo-Porto
- Oral Sciences Research Group, Special Needs Unit, Department of Surgery and Medical-Surgical Specialties, School of Medicine and Dentistry, Universidade de Santiago de Compostela, Health Research Institute of Santiago (IDIS), Santiago de Compostela, Spain
| | - C Balsa-Castro
- Oral Sciences Research Group, Special Needs Unit, Department of Surgery and Medical-Surgical Specialties, School of Medicine and Dentistry, Universidade de Santiago de Compostela, Health Research Institute of Santiago (IDIS), Santiago de Compostela, Spain
| | - P Castelo-Baz
- Oral Sciences Research Group, Special Needs Unit, Department of Surgery and Medical-Surgical Specialties, School of Medicine and Dentistry, Universidade de Santiago de Compostela, Health Research Institute of Santiago (IDIS), Santiago de Compostela, Spain
| | - L Nibali
- Periodontology Unit, Centre for Host-Microbiome Interactions, Dental Institute, King's College London, London, UK
| | - I Tomás
- Oral Sciences Research Group, Special Needs Unit, Department of Surgery and Medical-Surgical Specialties, School of Medicine and Dentistry, Universidade de Santiago de Compostela, Health Research Institute of Santiago (IDIS), Santiago de Compostela, Spain
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Foratori-Junior GA, Le Guennec A, Fidalgo TKDS, Jarvis J, Mosquim V, Buzalaf MAR, Carpenter GH, Sales-Peres SHDC. Comparison of the Metabolic Profile between Unstimulated and Stimulated Saliva Samples from Pregnant Women with/without Obesity and Periodontitis. J Pers Med 2023; 13:1123. [PMID: 37511736 PMCID: PMC10381358 DOI: 10.3390/jpm13071123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 07/08/2023] [Accepted: 07/09/2023] [Indexed: 07/30/2023] Open
Abstract
This study aimed to compare the metabolic profile of unstimulated (US) and stimulated (SS) saliva samples from pregnant women with/without obesity and periodontitis. Ninety-six pregnant women were divided into: obesity + periodontitis (OP = 20); obesity/no periodontitis (OWP = 27); normal BMI + periodontitis (NP = 20); and normal BMI/no periodontitis (NWP = 29). US and SS samples were collected by expectoration and chewing of sterilized parafilm gum, respectively, and samples were individually analyzed by Proton Nuclear Magnetic Resonance (1H-NMR). Univariate (t test and correlations) and multivariate (Principal Component Analysis-PCA, and Partial Least Square-Discriminant Analysis-PLS-DA with Variance Importance Projection-VIP scores) and Metabolite Set Enrichment Analysis were done (p < 0.05). Metabolites commonly found in all groups in elevated concentration in US samples were 5-Aminopentoate, Acetic acid, Butyric acid, Propionic acid, Pyruvic acid, and Succinic acid. They were mainly related to the butyrate metabolism, citric acid cycle, amino sugar metabolism, fatty acids biosynthesis, pyruvate metabolism, glutamate metabolism, and Warburg effect. Metabolites commonly found in all groups that were in elevated concentration in SS samples were Citrulline, Fumaric acid, Histidine, N-acetyl glutamine, N-acetylneuraminic acid, para-hydroxyphenylacetic acid, Proline, Tyrosine. Although some differences were found between unstimulated and stimulated saliva samples from pregnant women with/without obesity and periodontitis, stimulated saliva collection seems adequate, demonstrating similar metabolic pathways to unstimulated saliva samples when groups are compared.
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Affiliation(s)
- Gerson Aparecido Foratori-Junior
- Department of Pediatric Dentistry, Orthodontics and Public Health, Bauru School of Dentistry, University of São Paulo, Bauru 17012-901, Brazil
| | - Adrien Le Guennec
- Nuclear Magnetic Resonance Facility, Guy’s Campus, King’s College London, London SE1 1UL, UK
| | - Tatiana Kelly da Silva Fidalgo
- Department of Preventive and Community Dentistry, School of Dentistry, Rio de Janeiro State University, Rio de Janeiro 20551-030, Brazil
| | - James Jarvis
- Randall Division of Cell and Molecular Biophysics and Centre for Biomolecular Spectroscopy, Guy’s Campus, King’s College London, London SE1 1UL, UK
| | - Victor Mosquim
- Department of Operative Dentistry, Endodontics and Dental Materials, Bauru School of Dentistry, University of São Paulo, Bauru 17012-901, Brazil
| | | | - Guy Howard Carpenter
- Centre for Host-Microbiome Interactions, Faculty of Dental, Oral & Craniofacial Sciences, Guy’s Campus, King’s College London, London SE1 1UL, UK
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Li Y, Yang Z, Cai T, Jiang D, Luo J, Zhou Z. Untargeted metabolomics of saliva in caries-active and caries-free children in the mixed dentition. Front Cell Infect Microbiol 2023; 13:1104295. [PMID: 37082714 PMCID: PMC10110944 DOI: 10.3389/fcimb.2023.1104295] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 03/14/2023] [Indexed: 04/07/2023] Open
Abstract
ObjectiveTo compare the differences in salivary metabolites between caries-active and caries-free children in the mixed dentition, and explore their correlation with caries status.MethodsThe study involved 20 children (aged 8–9 years) in the mixed dentition, including 10 caries-active (aged 8.6 ± 0.49years) and 10 caries-free children(aged 8.5 ± 0.5years), with a male/female ratio of 1:1. The saliva samples were collected from all children. Metabolite extraction, LC-MS/MS-based untargeted metabolomics, qualitative and semi-quantitative analysis and bioinformatics analysis were performed to identify differential metabolites between the two sample groups. The differential metabolites identified were further analyzed in an attempt to find their correlations with caries status.ResultsIn the positive ion mode, a total of 1606 molecular features were detected in the samples of the two groups, 189 of which were differential metabolites when comparing the caries-active group with the caries-free group, including 104 up-regulated and 85 down-regulated metabolites. In the negative ion mode, a total of 532 molecular features were detected in the samples of two groups, 70 of which were differential metabolites when comparing the caries-active group with the caries-free group, including 37 up-regulated and 33 down-regulated metabolites. In the positive ion mode, two of the top 5 up-regulated differential metabolites were found in and annotated to specific metabolic pathways, whereas in the negative ion mode, only one of the top 5 up-regulated differential metabolites was found in and annotated to specific metabolic pathways. In both the positive and negative ion modes, the top 5 down-regulated differential metabolites were both annotated to the metabolic pathways. KEGG pathway enrichment analysis of differential metabolites showed that histamine and arachidonic acid identified in the positive ion mode, as well as succinate and L-histidine identified in the negative ion mode were enriched in the top 3 significantly altered pathways.ConclusionThe enriched differential metabolites including histamine, L-histidine and succinate were correlated with the presence of dental caries, but their role in the caries process needs to be further investigated.
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Affiliation(s)
- Yueheng Li
- Department of Preventive Dentistry, Stomatological Hospital of Chongqing Medical University, Chongqing, China
- College of Stomatology, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing, China
- Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing, China
| | - Zhengyan Yang
- Department of Preventive Dentistry, Stomatological Hospital of Chongqing Medical University, Chongqing, China
- College of Stomatology, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing, China
- Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing, China
| | - Ting Cai
- Department of Preventive Dentistry, Stomatological Hospital of Chongqing Medical University, Chongqing, China
- College of Stomatology, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing, China
- Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing, China
| | - Dan Jiang
- Department of Preventive Dentistry, Stomatological Hospital of Chongqing Medical University, Chongqing, China
- College of Stomatology, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing, China
- Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing, China
| | - Jun Luo
- Department of Preventive Dentistry, Stomatological Hospital of Chongqing Medical University, Chongqing, China
- College of Stomatology, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing, China
- Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing, China
- *Correspondence: Jun Luo, ; Zhi Zhou,
| | - Zhi Zhou
- Department of Preventive Dentistry, Stomatological Hospital of Chongqing Medical University, Chongqing, China
- College of Stomatology, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing, China
- Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing, China
- *Correspondence: Jun Luo, ; Zhi Zhou,
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Hyvärinen E, Kashyap B, Kullaa AM. Oral Sources of Salivary Metabolites. Metabolites 2023; 13:metabo13040498. [PMID: 37110157 PMCID: PMC10145445 DOI: 10.3390/metabo13040498] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 03/10/2023] [Accepted: 03/28/2023] [Indexed: 03/31/2023] Open
Abstract
The oral cavity is very diverse, where saliva plays an important role in maintaining oral health. The metabolism of saliva has been used to investigate oral diseases as well as general diseases, mainly to detect diagnostic biomarkers. There are many sources of salivary metabolites in the mouth. The online English language search and PubMed databases were searched to retrieve relevant studies on oral salivary metabolites. The physiological balance of the mouth is influenced by many factors that are reflected in the salivary metabolite profile. Similarly, the dysbiosis of microbes can alter the salivary metabolite profile, which may express oral inflammation or oral diseases. This narrative review highlights the factors to be considered when examining saliva and its use as a diagnostic biofluid for different diseases. Salivary metabolites, mainly small molecular metabolites may enter the bloodstream and cause illness elsewhere in the body. The importance of salivary metabolites produced in the oral cavity as risk factors for general diseases and their possible relationship to the body’s function are also discussed.
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Kim S, Song Y, Kim S, Kim S, Na H, Lee S, Chung J, Kim S. Identification of a Biomarker Panel for Diagnosis of Early Childhood Caries Using Salivary Metabolic Profile. Metabolites 2023; 13:metabo13030356. [PMID: 36984796 PMCID: PMC10052657 DOI: 10.3390/metabo13030356] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 02/25/2023] [Accepted: 02/25/2023] [Indexed: 03/06/2023] Open
Abstract
Several studies have demonstrated that nuclear magnetic resonance (NMR) metabolic profiles can differentiate patients with caries from healthy individuals; however, these studies only identified individual metabolites. The present study aimed to identify a salivary metabolite biomarker panel for the diagnosis of early childhood caries (ECC). Saliva samples from children with and without caries were analyzed using NMR spectroscopy. Multivariate and univariate analyses were performed to identify the discriminating metabolites. Selected metabolites were further evaluated and used to detect ECC. The saliva samples of children with ECC were characterized based on the increased levels of formate, glycerophosphocholine, and lactate and reduced levels of alanine, glycine, isoleucine, lysine, proline, and tyrosine. The levels of these metabolites were significantly different from those in the control in the ECC subgroup according to caries severity and correlated with the number of decayed and filled teeth or surfaces. Subsequently, an optimal salivary metabolite biomarker panel comprising formate, lactate, proline, and glycine was developed. This panel exhibited a better diagnostic performance for ECC than a single metabolite. These results demonstrate that salivary metabolic signatures can reflect oral conditions associated with dental caries, thereby emphasizing the importance of distinct salivary metabolic profiles as potential biomarkers of ECC.
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Affiliation(s)
- Seonghye Kim
- Department of Chemistry and Chemistry Institute for Functional Materials, Pusan National University, Busan 46241, Republic of Korea
| | - Yuri Song
- Department of Oral Microbiology, School of Dentistry, Pusan National University, Yangsan 50612, Republic of Korea
- Oral Genomics Research Center, Pusan National University, Yangsan 50612, Republic of Korea
| | - Seyeon Kim
- Department of Dental Hygiene, Jinju Health College, Jinju 52655, Republic of Korea
| | - Siyeong Kim
- Oral Genomics Research Center, Pusan National University, Yangsan 50612, Republic of Korea
- Dental Research Institute, BK21 PLUS Project, School of Dentistry, Pusan National University, Yangsan 50612, Republic of Korea
| | - Heesam Na
- Department of Oral Microbiology, School of Dentistry, Pusan National University, Yangsan 50612, Republic of Korea
- Oral Genomics Research Center, Pusan National University, Yangsan 50612, Republic of Korea
- Dental Research Institute, BK21 PLUS Project, School of Dentistry, Pusan National University, Yangsan 50612, Republic of Korea
| | - Sujin Lee
- Department of Chemistry and Chemistry Institute for Functional Materials, Pusan National University, Busan 46241, Republic of Korea
| | - Jin Chung
- Department of Oral Microbiology, School of Dentistry, Pusan National University, Yangsan 50612, Republic of Korea
- Oral Genomics Research Center, Pusan National University, Yangsan 50612, Republic of Korea
- Dental Research Institute, BK21 PLUS Project, School of Dentistry, Pusan National University, Yangsan 50612, Republic of Korea
- Correspondence: (J.C.); (S.K.)
| | - Suhkmann Kim
- Department of Chemistry and Chemistry Institute for Functional Materials, Pusan National University, Busan 46241, Republic of Korea
- Correspondence: (J.C.); (S.K.)
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Yang Y, Lv J, Bai H, Ren L, Yang J, Ding Y, Liu C, Chen X. Periodontal Status and Saliva Metabolic Signature in Patients with Alzheimer's Disease. J Alzheimers Dis 2023; 95:603-613. [PMID: 37424468 DOI: 10.3233/jad-230291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
BACKGROUND Characterizing the periodontal status of patients with Alzheimer's disease (AD), investigating differences in salivary metabolism between patients with and without AD under the same periodontal conditions, and understanding how it is related to oral flora are critical. OBJECTIVE We aimed to examine the periodontal condition of patients with AD and to screen salivary metabolic biomarkers from the saliva of individuals with and without AD with matched periodontal conditions. Furthermore, we aimed to explore the possible relationship between salivary metabolic changes and oral flora. METHODS In total, 79 individuals were recruited into the experiment for periodontal analysis. Especially, 30 saliva samples from the AD group and 30 from healthy controls (HCs) with matched periodontal conditions were selected for metabolomic analysis. The random-forest algorithm was used to detect candidate biomarkers. Among these, 19 AD saliva and 19 HC samples were selected to investigate the microbiological factors influencing the alterations in saliva metabolism in patients with AD. RESULTS The plaque index and bleeding on probing were considerably higher in the AD group. Further, Cis-3-(1-carboxy-ethyl)-3,5-cyclohexadiene-1,2-diol, dodecanoic acid, genipic acid, and N, N-dimethylthanolamine N-oxide were determined as candidate biomarkers, based on the area under the curve (AUC) value (AUC = 0.95). The results of oral-flora sequencing showed that dysbacteriosis may be a reason for the differences in AD saliva metabolism. CONCLUSION Dysregulation of the proportion of specific bacterial flora in saliva plays a vital role in metabolic changes in AD. These results will contribute to further improving the AD saliva biomarker system.
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Affiliation(s)
- Yi Yang
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Periodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China
| | - Jiaxi Lv
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Periodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China
| | - Huimin Bai
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Periodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China
| | - Liang Ren
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Periodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China
| | - Jing Yang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yi Ding
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Periodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China
| | - Chengcheng Liu
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Periodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China
| | - Xueping Chen
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
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11
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Foratori-Junior GA, Guennec AL, Fidalgo TKDS, Cleaver L, Buzalaf MAR, Carpenter GH, Sales-Peres SHDC. Metabolomic Profiles Associated with Obesity and Periodontitis during Pregnancy: Cross-Sectional Study with Proton Nuclear Magnetic Resonance ( 1H-NMR)-Based Analysis. Metabolites 2022; 12:metabo12111029. [PMID: 36355112 PMCID: PMC9694155 DOI: 10.3390/metabo12111029] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 10/18/2022] [Accepted: 10/24/2022] [Indexed: 12/27/2022] Open
Abstract
This study aimed to elucidate the metabolomic signature associated with obesity and periodontitis during pregnancy in plasma and saliva biofluids. Ninety-eight pregnant women were divided into: with obesity and periodontitis (OP = 20), with obesity but without periodontitis (OWP = 27), with normal BMI but with periodontitis (NP = 21), with normal BMI and without periodontitis (NWP = 30). Saliva and plasma were analyzed by 1H-NMR for metabolites identification. Partial Least Squares-Discriminant Analysis (PLS-DA), Sparse PLS-DA (sPLS-DA), and Variable Importance of Projection (VIP) were performed. ANOVA and Pearson’s correlation were applied (p < 0.05). Plasmatic analysis indicated the levels of glucose (p = 0.041) and phenylalanine (p = 0.015) were positively correlated with periodontal parameters and BMI, respectively. In saliva, periodontitis was mainly associated with high levels of acetic acid (p = 0.024), isovaleric acid, butyric acid, leucine, valine, isoleucine, and propionic acid (p < 0.001). High salivary concentrations of glycine (p = 0.015), succinic acid (p = 0.015), and lactate (p = 0.026) were associated with obesity. Saliva demonstrated a more elucidative difference than plasma, indicating the glucose-alanine cycle, alanine metabolism, valine, leucine and isoleucine degradation, glutamate metabolism, and Warburg effect as the main metabolic pathways.
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Affiliation(s)
- Gerson Aparecido Foratori-Junior
- Department of Pediatric Dentistry, Orthodontics and Public Health, Bauru School of Dentistry, University of São Paulo, Bauru 17012-901, Brazil
- Centre for Host-Microbiome Interactions, Faculty of Dental, Oral & Craniofacial Sciences, Guy’s Campus, King’s College London, London SE1 1UL, UK
- Correspondence: (G.A.F.-J.); (S.H.d.C.S.-P.)
| | - Adrien Le Guennec
- Nuclear Magnetic Resonance Facility, Guy’s Campus, King’s College London, London SE1 1UL, UK
| | - Tatiana Kelly da Silva Fidalgo
- Department of Preventive and Community Dentistry, School of Dentistry, Rio de Janeiro State University, Rio de Janeiro 20551-030, Brazil
| | - Leanne Cleaver
- Centre for Host-Microbiome Interactions, Faculty of Dental, Oral & Craniofacial Sciences, Guy’s Campus, King’s College London, London SE1 1UL, UK
| | | | - Guy Howard Carpenter
- Centre for Host-Microbiome Interactions, Faculty of Dental, Oral & Craniofacial Sciences, Guy’s Campus, King’s College London, London SE1 1UL, UK
| | - Silvia Helena de Carvalho Sales-Peres
- Department of Pediatric Dentistry, Orthodontics and Public Health, Bauru School of Dentistry, University of São Paulo, Bauru 17012-901, Brazil
- Correspondence: (G.A.F.-J.); (S.H.d.C.S.-P.)
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12
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Wei Y, Shi M, Nie Y, Wang C, Sun F, Jiang W, Hu W, Wu X. Integrated analysis of the salivary microbiome and metabolome in chronic and aggressive periodontitis: A pilot study. Front Microbiol 2022; 13:959416. [PMID: 36225347 PMCID: PMC9549375 DOI: 10.3389/fmicb.2022.959416] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 09/06/2022] [Indexed: 11/23/2022] Open
Abstract
This pilot study was designed to identify the salivary microbial community and metabolic characteristics in patients with generalized periodontitis. A total of 36 saliva samples were collected from 13 patients with aggressive periodontitis (AgP), 13 patients with chronic periodontitis (ChP), and 10 subjects with periodontal health (PH). The microbiome was evaluated using 16S rRNA gene high-throughput sequencing, and the metabolome was accessed using gas chromatography-mass spectrometry. The correlation between microbiomes and metabolomics was analyzed by Spearman’s correlation method. Our results revealed that the salivary microbial community and metabolite composition differed significantly between patients with periodontitis and healthy controls. Striking differences were found in the composition of salivary metabolites between AgP and ChP. The genera Treponema, Peptococcus, Catonella, Desulfobulbus, Peptostreptococcaceae_[XI] ([G-2], [G-3] [G-4], [G-6], and [G-9]), Bacteroidetes_[G-5], TM7_[G-5], Dialister, Eikenella, Fretibacterium, and Filifactor were present in higher levels in patients with periodontitis than in the healthy participants. The biochemical pathways that were significantly different between ChP and AgP included pyrimidine metabolism; alanine, aspartate, and glutamate metabolism; beta-alanine metabolism; citrate cycle; and arginine and proline metabolism. The differential metabolites between ChP and AgP groups, such as urea, beta-alanine, 3-aminoisobutyric acid, and thymine, showed the most significant correlations with the genera. These differential microorganisms and metabolites may be used as potential biomarkers to monitor the occurrence and development of periodontitis through the utilization of non-invasive and convenient saliva samples. This study reveals the integration of salivary microbial data and metabolomic data, which provides a foundation to further explore the potential mechanism of periodontitis.
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Affiliation(s)
- Yiping Wei
- Department of Periodontology, National Engineering Laboratory for Digital and Material Technology of Stomatology, NHC Research Center of Engineering and Technology for Computerized Dentistry, National Clinical Research Center for Oral Diseases, Peking University School and Hospital of Stomatology, Beijing, China
| | - Meng Shi
- Department of Periodontology, National Engineering Laboratory for Digital and Material Technology of Stomatology, NHC Research Center of Engineering and Technology for Computerized Dentistry, National Clinical Research Center for Oral Diseases, Peking University School and Hospital of Stomatology, Beijing, China
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yong Nie
- Laboratory of Environmental Microbiology, Department of Energy and Resources Engineering, College of Engineering, Peking University, Beijing, China
| | - Cui Wang
- Department of Periodontology, National Engineering Laboratory for Digital and Material Technology of Stomatology, NHC Research Center of Engineering and Technology for Computerized Dentistry, National Clinical Research Center for Oral Diseases, Peking University School and Hospital of Stomatology, Beijing, China
| | - Fei Sun
- Department of Periodontology, National Engineering Laboratory for Digital and Material Technology of Stomatology, NHC Research Center of Engineering and Technology for Computerized Dentistry, National Clinical Research Center for Oral Diseases, Peking University School and Hospital of Stomatology, Beijing, China
| | - Wenting Jiang
- Department of Periodontology, National Engineering Laboratory for Digital and Material Technology of Stomatology, NHC Research Center of Engineering and Technology for Computerized Dentistry, National Clinical Research Center for Oral Diseases, Peking University School and Hospital of Stomatology, Beijing, China
| | - Wenjie Hu
- Department of Periodontology, National Engineering Laboratory for Digital and Material Technology of Stomatology, NHC Research Center of Engineering and Technology for Computerized Dentistry, National Clinical Research Center for Oral Diseases, Peking University School and Hospital of Stomatology, Beijing, China
- *Correspondence: Wenjie Hu,
| | - Xiaolei Wu
- Laboratory of Environmental Microbiology, Department of Energy and Resources Engineering, College of Engineering, Peking University, Beijing, China
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The New Era of Salivaomics in Dentistry: Frontiers and Facts in the Early Diagnosis and Prevention of Oral Diseases and Cancer. Metabolites 2022; 12:metabo12070638. [PMID: 35888762 PMCID: PMC9319392 DOI: 10.3390/metabo12070638] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 06/27/2022] [Accepted: 07/06/2022] [Indexed: 12/22/2022] Open
Abstract
Nowadays, with the development of new and highly sensitive, blood is not the only medium of choice for the diagnosis of several diseases and pathological conditions. Saliva is now considered a safe and non-invasive sample to study oral and systemic diseases, showing great diagnostic potential. According to several recent studies, saliva has emerged as an emerging biofluid for the early diagnosis of several diseases, indicated as a mirror of oral and systemic health and a valuable source of clinically relevant information. Indeed, several studies have observed that saliva is useful for detecting and diagnosing malignant tumours, human immunodeficiency virus, heart disease, and autoimmune diseases. The growing realisation that saliva is an inexhaustible source of information has led to the coining of the term ‘Salivaomics’, which includes five “omics” in connection with the main constituents of saliva: genome and epigenome, transcriptomics, metabolomics, lipidomics, proteomics and microbiota. All those may be changed by disease state, so they offer significant advantages in the early diagnosis and prognosis of oral diseases. The aim of the present review isto update and highlight the new frontiers of salivaomics in diagnosing and managing oral disorders, such as periodontitis, premalignant disorders, and oral squamous cell carcinoma (OSCC).
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Panneerselvam K, Ishikawa S, Krishnan R, Sugimoto M. Salivary Metabolomics for Oral Cancer Detection: A Narrative Review. Metabolites 2022; 12:metabo12050436. [PMID: 35629940 PMCID: PMC9144467 DOI: 10.3390/metabo12050436] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 05/07/2022] [Accepted: 05/11/2022] [Indexed: 12/24/2022] Open
Abstract
The development of low- or non-invasive screening tests for cancer is crucial for early detection. Saliva is an ideal biofluid containing informative components for monitoring oral and systemic diseases. Metabolomics has frequently been used to identify and quantify numerous metabolites in saliva samples, serving as novel biomarkers associated with various conditions, including cancers. This review summarizes the recent applications of salivary metabolomics in biomarker discovery in oral cancers. We discussed the prevalence, epidemiologic characteristics, and risk factors of oral cancers, as well as the currently available screening programs, in India and Japan. These data imply that the development of biomarkers by itself is inadequate in cancer detection. The use of current diagnostic methods and new technologies is necessary for efficient salivary metabolomics analysis. We also discuss the gap between biomarker discovery and nationwide screening for the early detection of oral cancer and its prevention.
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Affiliation(s)
- Karthika Panneerselvam
- Department of Oral Pathology and Microbiology, Karpaga Vinayaga Institute of Dental Sciences, GST Road, Chinna Kolambakkam, Palayanoor PO, Madurantagam Taluk, Kancheepuram 603308, Tamil Nadu, India;
| | - Shigeo Ishikawa
- Department of Dentistry, Oral and Maxillofacial Plastic and Reconstructive Surgery, Faculty of Medicine, Yamagata University, Yamagata 990-9585, Japan;
| | - Rajkumar Krishnan
- Department of Oral Pathology, SRM Dental College, Bharathi Salai, Ramapuram, Chennai 600089, Tamil Nadu, India;
| | - Masahiro Sugimoto
- Institute of Medical Research, Tokyo Medical University, Tokyo 160-0022, Japan
- Institute for Advanced Biosciences, Keio University, Yamagata 997-0811, Japan
- Correspondence: ; Tel.: +81-235-29-0528
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Salivary Metabolomics for Diagnosis and Monitoring Diseases: Challenges and Possibilities. Metabolites 2021; 11:metabo11090587. [PMID: 34564402 PMCID: PMC8469343 DOI: 10.3390/metabo11090587] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 08/27/2021] [Accepted: 08/28/2021] [Indexed: 12/21/2022] Open
Abstract
Saliva is a useful biological fluid and a valuable source of biological information. Saliva contains many of the same components that can be found in blood or serum, but the components of interest tend to be at a lower concentration in saliva, and their analysis demands more sensitive techniques. Metabolomics is starting to emerge as a viable method for assessing the salivary metabolites which are generated by the biochemical processes in elucidating the pathways underlying different oral and systemic diseases. In oral diseases, salivary metabolomics has concentrated on periodontitis and oral cancer. Salivary metabolites of systemic diseases have been investigated mostly in the early diagnosis of different cancer, but also neurodegenerative diseases. This mini-review article aims to highlight the challenges and possibilities of salivary metabolomics from a clinical viewpoint. Furthermore, applications of the salivary metabolic profile in diagnosis and prognosis, monitoring the treatment success, and planning of personalized treatment of oral and systemic diseases are discussed.
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